Storage resource management method and program product for cloud edge collaboration

Abstract

The invention discloses a storage resource management method for cloud edge collaboration and a program product. The method comprises the following steps: acquiring multiple target storage resource parameters of a target edge node at multiple moments, and determining a first capacity quota of the target edge node according to the multiple target storage resource parameters at the multiple moments; generating a first token according to the first capacity quota, generating a first signature according to the first token, sending the first token to the target edge node, and receiving a second signature and a first storage resource sent by the target edge node, the first storage resource being determined according to the first token, the generation mode of the second signature is determined according to the generation mode of the first signature; and writing the first storage resource of the target edge node into a cloud resource scheduling center based on the first signature and the second signature. By analyzing the storage resource data of the edge nodes, more reasonable and effective storage resource allocation is realized, and the stability of the cloud edge collaborative system is effectively guaranteed.

Description

Technical Field

[0001] This invention relates to the field of intelligent storage resource management technology for cloud-edge collaboration, and in particular to a storage resource management method and program product for cloud-edge collaboration. Background Technology

[0002] In cloud-edge collaborative systems, the cloud resource scheduling center typically needs to schedule resources for multiple edge nodes. These edge nodes may contain a large amount of data that needs to be uploaded to the cloud resource scheduling center for centralized storage or archiving. Effectively managing storage resources and achieving efficient resource deployment and allocation are key to ensuring the performance of the collaborative system.

[0003] In related technologies, common storage resource management methods usually rely on static configuration or a simple "apply first, use later" approach to manage the uploading and sending of resources at each edge node. However, such methods cannot respond to real-time data traffic changes in a timely manner and cannot achieve efficient utilization of storage resources. Therefore, current technologies are insufficient in high-concurrency scenarios and cannot meet the needs of effective allocation and management of storage resources. Summary of the Invention

[0004] This invention provides a storage resource management method and program product for cloud-edge collaboration, which solves the latency and overhead problems of storage resource application in cloud-edge collaboration systems, thereby enabling dynamic allocation and management of storage resources to effectively meet high-concurrency and low-latency usage scenarios.

[0005] According to one aspect of the present invention, a storage resource management method for cloud-edge collaboration is provided, applied to a cloud resource scheduling center, the method comprising:

[0006] The target edge node acquires multiple target storage resource parameters at multiple times, and determines a first capacity quota for the target edge node based on the multiple target storage resource parameters at multiple times. The first capacity quota is used to indicate the total resource storage of the target edge node in the cloud resource scheduling center.

[0007] A first token is generated based on the first capacity quota, a first signature is generated based on the first token, the first token is sent to the target edge node, and a second signature and a first storage resource are received from the target edge node, wherein the first storage resource is determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature.

[0008] The first storage resource of the target edge node is written to the cloud resource scheduling center based on the first signature and the second signature.

[0009] According to another aspect of the present invention, a storage resource management device for cloud-edge collaboration is provided, applied to a cloud resource scheduling center, the device comprising:

[0010] The capacity allocation module is used to obtain multiple target storage resource parameters of the target edge node at multiple times, and determine the first capacity quota of the target edge node based on the multiple target storage resource parameters at multiple times. The first capacity quota is used to indicate the total resource storage of the target edge node in the cloud resource scheduling center.

[0011] The token distribution module is used to generate a first token according to the first capacity quota, generate a first signature according to the first token, send the first token to the target edge node, and receive a second signature and a first storage resource sent by the target edge node, wherein the first storage resource is determined according to the first token and the generation method of the second signature is determined according to the generation method of the first signature.

[0012] The resource storage module is used to generate a second signature based on the first token sent by the target edge node, and to write the first storage resource of the target edge node into the cloud resource scheduling center based on the first signature and the second signature.

[0013] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0014] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to execute a storage resource management method for cloud-edge collaboration as described in any embodiment of the present invention.

[0015] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a processor to execute and implement a storage resource management method for cloud-edge collaboration as described in any embodiment of the present invention.

[0016] According to another aspect of the present invention, embodiments of the present disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements a storage resource management method for cloud-edge collaboration as described in any of the embodiments of the present disclosure.

[0017] The technical solution of this invention firstly involves acquiring multiple target storage resource parameters of a target edge node at multiple times, and determining a first capacity quota for the target edge node based on these parameters. This first capacity quota indicates the total resource storage capacity of the target edge node in the cloud resource scheduling center. This allows for the allocation of a more reasonable and matching first capacity quota based on the edge node's storage resource usage data, reducing resource application overhead and communication traffic consumption. Secondly, a first token is generated based on the first capacity quota, and a first signature is generated based on the first token. The first token is then sent to the target edge node. Additionally, a second signature and first storage resources are received from the target edge node. The first storage resources are determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature. The generated token controls the uploading of storage resources by each edge node, allowing the edge node to focus on the generation and uploading of resource data, thus improving the security and convenience of resource transmission. Finally, based on the first signature and the second signature, the first storage resource of the target edge node is written to the cloud resource scheduling center. The verification and comparison of the first and second signatures effectively ensures the legality, compliance, and validity of the uploaded storage resource. Therefore, this technical solution, by employing the above-mentioned technical means, can achieve reasonable allocation and management of edge node storage resources in high-concurrency application scenarios through a cloud-edge collaborative system, and provide security protection for storage resource transmission, thereby ensuring the stability of the cloud-edge collaborative system.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of a storage resource management method for cloud-edge collaboration provided according to Embodiment 1 of the present invention;

[0021] Figure 2 This is a flowchart of a storage resource management method for cloud-edge collaboration provided according to Embodiment 2 of the present invention;

[0022] Figure 3 This is a preferred implementation flowchart of a storage resource management method for cloud-edge collaboration provided in Embodiment 3 of the present invention;

[0023] Figure 4 This is a schematic diagram of a storage resource management device for cloud-edge collaboration provided in Embodiment 4 of the present invention;

[0024] Figure 5 This is a schematic diagram of the structure of an electronic device that implements the storage resource management method for cloud-edge collaboration provided in Embodiment 5 of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0028] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0029] It is understood that before using the technical solutions disclosed in the various embodiments of this disclosure, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in this disclosure in an appropriate manner in accordance with relevant laws and regulations, and user authorization should be obtained.

[0030] For example, upon receiving a user's active request, a prompt message is sent to the user to explicitly inform them that the requested operation will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to the software or hardware, such as the electronic device, application, server, or storage medium performing the operations of this disclosed technical solution, based on the prompt message.

[0031] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0032] It is understood that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of this disclosure.

[0033] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and related provisions.

[0034] Example 1

[0035] Figure 1 This is a flowchart illustrating a cloud-edge collaborative storage resource management method according to Embodiment 1 of the present invention. This embodiment is applicable to software-defined cloud-edge collaborative control systems, particularly to cloud resource scheduling center servers and edge devices in high-concurrency scenarios. Specifically, this technical solution can be applied to a cloud resource scheduling center. This method can be executed by a storage resource management device for cloud-edge collaboration. This storage resource management device for cloud-edge collaboration can be implemented in hardware and / or software, optionally through electronic devices, such as mobile terminals, PCs, or servers. Figure 1 As shown, the method may specifically include:

[0036] S110. Obtain multiple target storage resource parameters of the target edge node at multiple times, and determine the first capacity quota of the target edge node based on the multiple target storage resource parameters at multiple times. The first capacity quota is used to indicate the total resource storage of the target edge node in the cloud resource scheduling center.

[0037] The target edge node can be understood as an edge server or device that requires storage resource capacity allocation. Various target storage resource parameters may include at least one of the following: average read / write speed, peak read / write speed, transmission latency, and transmission success rate.

[0038] Specifically, the cloud resource scheduling center can continuously collect various target storage resource parameters from each edge node at multiple times. By inputting these parameters into a pre-trained capacity quota model, the model outputs valid first capacity quota data for a specific period corresponding to the target edge node. Based on this capacity quota data, the target edge node can continue its storage resource transfer operations. By analyzing capacity quotas using historical storage resource data from edge nodes, the model can effectively improve the rationality of allocating storage resource capacity to target edge nodes, thereby achieving efficient utilization of storage resources and reducing the frequency of edge nodes requesting capacity quotas from the cloud resource scheduling center, thus reducing communication traffic overhead.

[0039] S120. Generate a first token based on the first capacity quota, generate a first signature based on the first token, send the first token to the target edge node, and receive a second signature and a first storage resource sent by the target edge node, wherein the first storage resource is determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature.

[0040] The first token can be understood as a digital credential generated by the resource scheduling center, which can encapsulate information such as the authorized amount and validity period of the first capacity quota. The first signature can be understood as ciphertext data formed by encrypting the first token using a private key, used to ensure the security of token transmission. The second signature can be understood as ciphertext data formed by encrypting and signing the first token data and the attribute information of the edge node using a private key, used to ensure the security of resource transmission. The first storage resource can be understood as data that needs to be uploaded to the cloud resource scheduling center.

[0041] Specifically, based on the first capacity quota allocated by the cloud resource scheduling center, the validity period timestamp, and data information related to the target edge node, a first token corresponding to the target edge node is generated. The obtained first token is identified and signed to generate a first signature, which is then stored in the cloud resource scheduling center. The generated first token is sent to the target edge node, allowing it to update its capacity configuration and other information based on the first token. It can also receive a second signature and first storage resources from the target edge node, thereby storing the first storage resources through signature verification. This technical solution, by generating tokens to update the capacity quota of edge nodes and receiving resource storage from edge nodes, effectively ensures the normal data storage and uploading of edge nodes, improving the stability of the cloud-edge collaborative system.

[0042] In one implementation, generating the first token based on the first capacity quota includes: obtaining the edge node identifier, token validity period, and token identifier of the target edge node, and generating the first token based on the first capacity quota, the edge node identifier, the token validity period, and the token identifier.

[0043] Specifically, the cloud resource scheduling center can obtain the edge node identifier associated with the target edge node and assign corresponding parameters such as token validity period and token identifier to the token. This allows for the generation of a first token corresponding to the target edge node based on parameters such as the first capacity quota, edge node identifier, token validity period, and token identifier. The generated token enables precise edge node capacity quota allocation and effectively improves the security of token distribution and the compliance of storage resource allocation.

[0044] In another implementation, generating a first signature based on the first token includes: converting the first token into a first string of a preset format, performing a hash calculation on the first string to obtain a first digest, and signing the first digest with a private key to obtain a first signature.

[0045] The preset format can include at least one of the following: structured text format (JSON format), key-value pair format, CSV format, etc. The first summary can be understood as the calculated hash value result.

[0046] Specifically, the content of the first token can be converted into a first string of data in JSON format. This first string is then hashed and encrypted to obtain an encrypted first digest. The first digest is then signed and encrypted using the private key of the cloud resource scheduling center to generate a first signature. This first signature is stored in the cloud resource scheduling center for subsequent storage verification. This method allows for the pre-providing of encrypted verification data to each edge node, enabling more efficient signature verification and improving the efficiency and security of resource storage.

[0047] In one implementation, the target edge node sends the second signature and the first storage resource as follows: In response to receiving the first token, the target edge node verifies the validity of the first token based on the token validity period in the received first token; if the first token is valid, the target edge node determines the first storage resource based on the first capacity quota in the first token, and generates the second signature based on the received first token; and sends the first storage resource and the second signature to the cloud resource scheduling center.

[0048] Specifically, when the target edge node receives the first token, it can parse the token to verify it based on the parsed token's validity period and / or the first capacity quota. If the first token is valid, the target edge node can determine the first storage resource that meets the requirements based on the first capacity quota within the first token. It can also construct a structured second token based on the parsed first token information and the target edge node's attribute information, and generate a second signature using this second token. Finally, the determined first storage resource and the second signature can be sent to the cloud resource scheduling center to complete the upload of the first storage resource. By adopting this method, secure, efficient, and controllable data transmission of storage resources by edge nodes can be achieved, effectively improving the overall coordination of the cloud-edge collaborative system.

[0049] In one implementation, generating a second signature based on the received first token includes: converting the first token into a second string in the preset format; performing a hash calculation based on the attribute information of the target edge node and the second string to obtain a second digest; and signing the second digest with the private key to obtain a second signature.

[0050] The second string can be understood as attribute information, which typically includes the node identifier and public key of the edge node. The second digest is the same as the first digest, and can also be understood as the calculated hash value.

[0051] Specifically, the received first token is converted into a second string in a preset format, and the data information contained in the first token is determined. Then, a hash calculation is performed on the target edge node's attribute information and the second string data to obtain a second digest representing the target edge node. Finally, the second digest is signed using the target edge node's private key to obtain a second signature result. By adopting this technical approach, the traceability of edge node storage resource transmission can be enhanced through signature verification, enabling edge nodes to achieve autonomous, secure, and reliable storage resource transmission, thereby improving the stability of the cloud-edge collaborative system.

[0052] In another implementation, after generating the first token according to the first capacity quota, the method further includes: updating the first token in response to satisfying the update conditions for the first token for the target edge node, wherein the update conditions include at least one of the following: the first capacity quota changes, the first token expires, the amount of resources stored by the target edge node in the cloud resource scheduling center reaches a preset capacity threshold, and the actual usage of the first capacity quota by the target edge node during the validity period of the first token reaches a preset usage threshold.

[0053] Specifically, edge nodes can monitor the status of the first token in real time. When at least one of the following occurs: the first capacity quota changes, the first token expires, the target edge node's stored resources in the cloud resource scheduling center reach a preset capacity threshold, or the target edge node's actual usage of the first capacity quota within the first token's validity period reaches a preset usage threshold, the target edge node can send a token update request to the cloud resource scheduling center to update the target edge node's first token. The cloud resource scheduling center can update the first token by responding to the update conditions included in the target edge node's token update request, ensuring that the target edge node can continue to transmit storage resources. By setting certain update conditions, the continuous transmission of storage resources by edge nodes can be effectively guaranteed, and the frequency of token distribution requests between the cloud resource scheduling center and edge nodes can be effectively reduced, allowing the target edge node to focus more on data collection and transmission.

[0054] S130. Based on the first signature and the second signature, write the first storage resource of the target edge node into the cloud resource scheduling center.

[0055] Specifically, by parsing the first and second signatures to determine the consistency of the parsed data content, the first storage resource sent by the matching target edge node is written into the cloud resource scheduling center. Verifying the encrypted signature improves the security and timeliness of storage resource usage, preventing the abuse of storage resources.

[0056] The technical solution of this invention firstly involves acquiring multiple target storage resource parameters of a target edge node at multiple times, and determining a first capacity quota for the target edge node based on these parameters. This first capacity quota indicates the total resource storage capacity of the target edge node in the cloud resource scheduling center. This allows for the allocation of a more reasonable and matching first capacity quota based on the edge node's storage resource usage data, reducing resource application overhead and communication traffic consumption. Secondly, a first token is generated based on the first capacity quota, and a first signature is generated based on the first token. The first token is then sent to the target edge node. Additionally, a second signature and first storage resources are received from the target edge node. The first storage resources are determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature. The generated token controls the uploading of storage resources by each edge node, allowing the edge node to focus on the generation and uploading of resource data, thus improving the security and convenience of resource transmission. Finally, based on the first signature and the second signature, the first storage resource of the target edge node is written to the cloud resource scheduling center. The verification and comparison of the first and second signatures effectively ensures the legality, compliance, and validity of the uploaded storage resource. Therefore, this technical solution, by employing the above-mentioned technical means, can achieve reasonable allocation and management of edge node storage resources in high-concurrency application scenarios through a cloud-edge collaborative system, and provide security protection for storage resource transmission, thereby ensuring the stability of the cloud-edge collaborative system.

[0057] Example 2

[0058] Figure 2 This is a flowchart of a storage resource management method for cloud-edge collaboration provided in Embodiment 2 of the present invention. This embodiment is a refinement of the technical solution for writing the first storage resource of the target edge node into the cloud resource scheduling center based on the first signature and the second signature, based on the above embodiments. Detailed implementation can be found in the description of this embodiment. Technical features that are the same as or similar to those in the foregoing embodiments will not be repeated here. Figure 2 As shown, the method may specifically include:

[0059] S210. Obtain multiple target storage resource parameters of the target edge node at multiple times, and determine the first capacity quota of the target edge node based on the multiple target storage resource parameters at multiple times. The first capacity quota is used to indicate the total resource storage of the target edge node in the cloud resource scheduling center.

[0060] S220. Generate a first token based on the first capacity quota, generate a first signature based on the first token, send the first token to the target edge node, and receive a second signature and a first storage resource sent by the target edge node, wherein the first storage resource is determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature.

[0061] S230. The first signature and the second signature are decrypted using the public key corresponding to the private key to determine the first digest and the second digest.

[0062] Specifically, the cloud resource scheduling center can directly parse the first and second signatures using a pre-stored public key corresponding to the private key, thereby determining the corresponding first and second digests. Alternatively, it can parse the first signature using a pre-stored public key corresponding to the private key to determine the first digest; and use the public key information sent by the target edge node to determine the public key for parsing the second signature, thus determining the second digest based on that public key. Through digest parsing, the compliance and legality of storage resource transmission can be effectively verified, improving the protection of storage resources and the security of the cloud-edge collaborative system.

[0063] S240. In response to the first digest being the same as the second digest, determine the amount of resources already stored by the target edge node in the cloud resource scheduling center and the amount of storage to be occupied corresponding to the first storage resource, and determine the remaining storage amount based on the first capacity quota and the amount of resources already stored.

[0064] The stored resource amount can be understood as the resource storage amount recorded when the target edge node transmits storage resources. The storage amount to be occupied can be understood as the data amount of storage resources in the current transmission. The remaining storage amount can be understood as the data amount of storage resources that the target edge node can still transmit within the validity period of the first token.

[0065] Specifically, the parsed first digest and second digest are compared. If they match, the amount of resources already stored by the target edge node in the cloud resource scheduling center, and the amount of storage to be occupied corresponding to the first storage resource in the current batch, are obtained. The remaining storage amount of the target edge node in the cloud resource scheduling center is determined by subtracting the first capacity quota marked in the first token from the amount of stored resources. By determining the amount of data that the target edge node can store, the problem of insufficient storage due to excessive storage resources is avoided, ensuring the smooth storage of storage resources.

[0066] Furthermore, before performing digest comparison and matching, the transmission time of the target edge node in the current batch of storage resource data can be determined first, and then matched with the token validity period to ensure the compliance and legality of storage resource transmission, and further guarantee the smooth transmission of storage resources.

[0067] S250. In response to the fact that the amount of storage to be occupied corresponding to the first storage resource is less than or equal to the remaining storage amount, the first storage resource is written to the cloud resource scheduling center.

[0068] Specifically, the amount of storage to be occupied and the amount of remaining storage are compared. When the amount of storage to be occupied is less than or equal to the amount of remaining storage, the first storage resource is written to the cloud resource scheduling center, thereby completing the upload operation of the storage resource.

[0069] In another implementation, after writing the first storage resource to the cloud resource scheduling center, the method further includes: updating the amount of stored resources of the target edge node in the cloud resource scheduling center.

[0070] Specifically, after the storage resources are uploaded, the amount of stored resources at the current batch time can be added to the amount of storage to be used, thereby calculating the latest real-time stored resource amount of the target edge node in the cloud resource scheduling center after the upload is completed. Timely data updates facilitate subsequent resource uploads to the target edge node, ensuring the accuracy of the transmitted resource amount.

[0071] The technical solution of this invention decrypts the first signature and the second signature using the public key corresponding to the private key, respectively, to determine the first digest and the second digest, thereby ensuring the security of storage resources. In response to the first digest and the second digest being the same, the amount of resources already stored by the target edge node in the cloud resource scheduling center and the amount of storage to be occupied corresponding to the first storage resource are determined, and the remaining storage amount is determined based on the first capacity quota and the amount of stored resources; thus, storage resources can be executed promptly and smoothly based on data volume matching, improving data storage efficiency. In response to the amount of storage to be occupied corresponding to the first storage resource being less than or equal to the remaining storage amount, the first storage resource is written to the cloud resource scheduling center, thereby enabling the first storage resource to be successfully written to the cloud resource scheduling center when preset conditions are met, achieving efficient and secure storage of storage resources.

[0072] Example 3

[0073] Embodiment 3 of the present invention provides a flowchart of a storage resource management method for cloud-edge collaboration. To better illustrate the technical solution provided by this embodiment, this embodiment uses the specific interaction between the cloud resource scheduling center and edge nodes as an example. The flowchart of this embodiment is as follows: Figure 3 As shown, specific implementation methods can be found in the description of this embodiment. Technical features that are the same as or similar to those in the foregoing embodiments will not be repeated here.

[0074] Specifically, the overall implementation process is as follows: Figure 3 As shown.

[0075] 1. Token Generation

[0076] The cloud resource scheduling center continuously collects historical storage usage data from each edge node, including but not limited to: the average hourly write volume, peak write volume, and variance of write requests over the past 24 hours or 7 days. Based on the quota calculation model, it estimates a capacity quota that can be provided in the short term and generates the first token based on the edge node identifier, capacity quota information, validity period timestamp, and token identifier.

[0077] 2. Signature generation

[0078] The content of the first token is formatted as JSON and then hashed (e.g., using SHA-256) to obtain a fixed-length first digest. The cloud resource scheduling center signs the first digest using its private key (the corresponding public key is stored in the cloud resource scheduling center's storage gateway) to generate the first signature, and then stores the first signature in the cloud resource scheduling center.

[0079] 3. Secure token distribution

[0080] The cloud resource scheduling center periodically pushes the generated first token to the edge nodes through an encrypted channel.

[0081] 4. Token processing at edge nodes

[0082] Upon receiving the first token, the edge node first verifies its origin (via a TLS certificate) and integrity (by checking the JSON format). Then, it stores the first token information locally and starts a timer to monitor its validity period. If the first token is valid, it identifies eligible resource data to be uploaded based on its restrictions. A hash calculation is then performed based on the first token and the edge node's attribute information to obtain a second digest. This second digest is then encrypted using the same private key as in the previous steps to determine a second signature. The resource data to be uploaded and the second signature are then combined and sent to the cloud resource scheduling center as the write request body.

[0083] 5. Cloud Resource Scheduling Center Token Verification and Write Control

[0084] The storage gateway of the cloud resource scheduling center receives a write request body containing resource data and a second signature. It extracts the second signature data from the write request body and decodes the first and second signatures using a pre-configured public key corresponding to the private key to obtain a first digest and a second digest. If the first digest and the second digest match, it indicates that the first token data of the edge node is valid.

[0085] The system checks the used quota of the edge node within the current validity period timestamp and calculates the remaining quota: the remaining quota equals the token-allocated capacity quota minus the used quota, and confirms that the remaining quota is greater than or equal to the size of the data to be written. If the verification passes, the resource storage gateway module of the cloud resource scheduling center allows the writing of the resource data to be uploaded and modifies the used quota: the used quota equals the used quota value before writing plus the write value corresponding to the resource data to be uploaded.

[0086] 6. Token Update

[0087] Edge nodes: Edge nodes can monitor token status in real time through local agents. When the remaining quota is below the threshold (e.g., 10%) or nearing the expiration time (e.g., 5 minutes remaining), a token update request is sent to the cloud resource scheduling center.

[0088] Cloud Resource Scheduling Center: Generates and issues new tokens based on the newly calculated capacity quota, or requires edge nodes to report their actual usage of the capacity quota during the current token cycle, so as to generate new tokens based on the calibrated model.

[0089] This technical solution effectively reduces the communication overhead of edge nodes requesting storage resources by employing the aforementioned technical means. Furthermore, by allocating reasonable capacity quotas to edge nodes, it enables them to cope with data bursts in storage resources, thereby achieving security protection and efficient and reasonable allocation and management of storage resources.

[0090] Example 4

[0091] Figure 4 This is a schematic diagram of a storage resource management device for cloud-edge collaboration provided in Embodiment 4 of the present invention. Figure 4 As shown, the storage resource management device can be configured in a cloud resource scheduling center. Specifically, the storage resource management device may include: a capacity allocation module 401, a token distribution module 402, and a resource storage module 403.

[0092] The capacity allocation module 401 is used to acquire multiple target storage resource parameters of the target edge node at multiple times, determine a first capacity quota for the target edge node based on the multiple target storage resource parameters at multiple times, and the first capacity quota is used to indicate the total resource storage amount of the target edge node in the cloud resource scheduling center. The token distribution module 402 is used to generate a first token based on the first capacity quota, generate a first signature based on the first token, send the first token to the target edge node, and receive a second signature and a first storage resource sent by the target edge node, where the first storage resource is determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature. The resource storage module 403 is used to write the first storage resource of the target edge node into the cloud resource scheduling center based on the first signature and the second signature.

[0093] The technical solution of this invention involves the following steps: First, the capacity allocation module 401 acquires multiple target storage resource parameters of the target edge node at multiple times, and determines a first capacity quota for the target edge node based on these parameters. This first capacity quota indicates the total resource storage amount of the target edge node in the cloud resource scheduling center. This allows for the allocation of a more reasonable and matching first capacity quota based on the storage resource usage data of the edge node, reducing resource application overhead and communication traffic consumption. Second, the token distribution module 402 generates a first token based on the first capacity quota, generates a first signature based on the first token, sends the first token to the target edge node, and receives a second signature and first storage resource from the target edge node. The first storage resource is determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature. The generated token controls the uploading of storage resources by each edge node, allowing the edge node to focus on the generation and uploading of resource data, thus improving the security and convenience of resource transmission. Finally, the resource storage module 403 writes the first storage resource of the target edge node into the cloud resource scheduling center based on the first signature and the second signature. The verification and comparison of the first and second signatures effectively ensures the legality, compliance, and validity of the uploaded storage resources. Therefore, this technical solution, by employing the above-mentioned technical means, can achieve reasonable allocation and management of edge node storage resources in high-concurrency application scenarios through a cloud-edge collaborative system, and provide security protection for storage resource transmission, thereby ensuring the stability of the cloud-edge collaborative system.

[0094] Optionally, based on the above-mentioned optional technical solutions, the token distribution module 402 may further include: a first token generation unit. The first token generation unit is configured to obtain the edge node identifier, token validity period, and token identifier of the target edge node, and generate a first token based on the first capacity quota, the edge node identifier, the token validity period, and the token identifier.

[0095] Based on the above-mentioned optional technical solutions, the token distribution module 402 may optionally include: a first signature generation unit and a second signature generation unit. The first signature generation unit is configured to convert the first token into a first string of a preset format, perform a hash calculation on the first string to obtain a first digest, and sign the first digest using a private key to obtain a first signature.

[0096] Based on the above-mentioned optional technical solutions, the resource storage module 403 may optionally include: a digest parsing unit, a remaining space determination unit, and a resource writing unit. The digest parsing unit is used to decrypt the first signature and the second signature using the public key corresponding to the private key, respectively, to determine the first digest and the second digest. The remaining space determination unit is used to determine the amount of resources already stored by the target edge node in the cloud resource scheduling center and the amount of storage to be occupied corresponding to the first storage resource in response to the first digest being the same as the second digest, and to determine the remaining storage space based on the first capacity quota and the amount of resources already stored. The resource writing unit is used to write the first storage resource into the cloud resource scheduling center in response to the remaining storage space corresponding to the first storage resource being less than or equal to the remaining storage space.

[0097] Based on the above-mentioned optional technical solutions, the storage resource management device for cloud-edge collaboration may optionally include: a resource storage quantity update module. The resource storage quantity update module is used to update the amount of resources already stored by the target edge node in the cloud resource scheduling center after the first storage resource is written to the cloud resource scheduling center.

[0098] Based on the above-mentioned optional technical solutions, optionally, the method by which the target edge node sends the second signature and the first storage resource may include: a token verification unit, a transmission resource determination unit, and a transmission resource sending unit. Specifically, the token verification unit is configured to, in response to an event of receiving the first token, verify the validity of the first token based on the token validity period in the received first token; the transmission resource determination unit is configured to, when the first token is valid, determine the first storage resource based on the first capacity quota in the first token, and generate a second signature based on the received first token; the transmission resource sending unit is configured to send the first storage resource and the second signature to the cloud resource scheduling center.

[0099] Optionally, based on the above-mentioned optional technical solutions, the transmission resource determination unit may further include: a second signature generation unit. The second signature generation unit is configured to convert the first token into the second string of the preset format, perform hash calculation based on the attribute information of the target edge node and the second string to obtain a second digest, and sign the second digest using the private key to obtain a second signature.

[0100] Based on the above-mentioned optional technical solutions, the storage resource management device for cloud-edge collaboration may optionally include a token update module. The token update module is configured to update the first token in response to meeting update conditions for the first token of the target edge node. The update conditions include at least one of the following: a change in the first capacity quota, the first token becoming invalid, the amount of resources stored by the target edge node in the cloud resource scheduling center reaching a preset capacity threshold, and the actual usage of the first capacity quota by the target edge node within the validity period of the first token reaching a preset usage threshold.

[0101] Based on the above-mentioned optional technical solutions, the multiple target storage resource parameters may optionally include at least one of the following parameters: average read / write speed, peak read / write speed, transmission latency, and transmission success rate.

[0102] The storage resource management device for cloud-edge collaboration provided in this embodiment of the invention can execute a storage resource management method for cloud-edge collaboration provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing a storage resource management method for cloud-edge collaboration. Technical details not described in detail in this embodiment can be found in any of the storage resource management methods for cloud-edge collaboration described in this embodiment of the invention.

[0103] Example 5

[0104] Figure 5 A schematic diagram of an electronic device 10, which can be used to implement embodiments of the present invention, is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0105] like Figure 5As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0106] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0107] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a storage resource management method for cloud-edge collaboration.

[0108] In some embodiments, a storage resource management method for cloud-edge collaboration can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the storage resource management method for cloud-edge collaboration described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform a storage resource management method for cloud-edge collaboration by any other suitable means (e.g., by means of firmware).

[0109] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0110] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0111] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0112] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0113] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0114] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0115] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication unit 19, or installed from storage unit 18, or installed from ROM 12. When the computer program is executed by processor 11, it performs the functions defined in the methods of the embodiments of the present invention.

[0116] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0117] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A storage resource management method for cloud-edge collaboration, characterized in that, Applications include cloud-based resource scheduling centers, including: The target edge node acquires multiple target storage resource parameters at multiple times, and determines a first capacity quota for the target edge node based on the multiple target storage resource parameters at multiple times. The first capacity quota is used to indicate the total resource storage of the target edge node in the cloud resource scheduling center. A first token is generated based on the first capacity quota, a first signature is generated based on the first token, the first token is sent to the target edge node, and a second signature and a first storage resource are received from the target edge node, wherein the first storage resource is determined based on the first token, and the generation method of the second signature is determined based on the generation method of the first signature. The first storage resource of the target edge node is written to the cloud resource scheduling center based on the first signature and the second signature.

2. The storage resource management method for cloud-edge collaboration according to claim 1, characterized in that, The step of generating the first token based on the first capacity quota includes: Obtain the edge node identifier, token validity period, and token identifier of the target edge node, and generate a first token based on the first capacity quota, the edge node identifier, the token validity period, and the token identifier.

3. The storage resource management method for cloud-edge collaboration according to claim 1, characterized in that, The step of generating the first signature based on the first token includes: The first token is converted into a first string in a preset format, the first string is hashed to obtain a first digest, and the first digest is signed with a private key to obtain a first signature.

4. The storage resource management method for cloud-edge collaboration according to claim 1, characterized in that, The step of writing the first storage resource of the target edge node into the cloud resource scheduling center based on the first signature and the second signature includes: The first digest and the second digest are determined by decrypting the first signature and the second signature using the public key corresponding to the private key, respectively. In response to the first digest being the same as the second digest, the amount of resources already stored by the target edge node in the cloud resource scheduling center and the amount of storage to be occupied corresponding to the first storage resource are determined, and the remaining storage amount is determined according to the first capacity quota and the amount of resources already stored; In response to the fact that the amount of storage to be occupied corresponding to the first storage resource is less than or equal to the amount of remaining storage, the first storage resource is written to the cloud resource scheduling center.

5. The storage resource management method for cloud-edge collaboration according to claim 4, characterized in that, After writing the first storage resource to the cloud resource scheduling center, the method further includes: Update the amount of resources already stored in the cloud resource scheduling center for the target edge node.

6. The storage resource management method for cloud-edge collaboration according to claim 1, characterized in that, The target edge node sends the second signature and the first storage resource in the following manner: In response to receiving the first token, the target edge node verifies the validity of the first token based on the token validity period in the received first token; If the first token is valid, the first storage resource is determined based on the first capacity quota in the first token, and a second signature is generated based on the received first token. The first storage resource and the second signature are sent to the cloud resource scheduling center.

7. The storage resource management method for cloud-edge collaboration according to claim 6, characterized in that, The step of generating a second signature based on the received first token includes: The first token is converted into the second string in the preset format. A hash calculation is performed based on the attribute information of the target edge node and the second string to obtain a second digest. The second digest is then signed using the private key to obtain a second signature.

8. The storage resource management method for cloud-edge collaboration according to claim 1, characterized in that, After generating the first token based on the first capacity quota, the method further includes: In response to meeting the update conditions for the first token of the target edge node, the first token is updated. The update conditions include at least one of the following: the first capacity quota changes, the first token expires, the amount of resources stored by the target edge node in the cloud resource scheduling center reaches a preset capacity threshold, and the actual usage of the first capacity quota by the target edge node during the validity period of the first token reaches a preset usage threshold.

9. The storage resource management method for cloud-edge collaboration according to claim 1, characterized in that, The various target storage resource parameters include at least one of the following: average read / write speed, peak read / write speed, transmission latency, and transmission success rate.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the storage resource management method for cloud-edge collaboration as described in any one of claims 1-9.

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